Italian Institute of Technology

Krabbe disease (KD) is a neurodegenerative disorder caused by the lack of β- galactosylceramidase enzymatic activity and by widespread accumulation of the cytotoxic galactosyl-sphingosine in neuronal, myelinating and endothelial cells. Despite the wide use of Twitcher mice as experimental model for KD, the ultrastructure of this model is partial and mainly addressing peripheral nerves. More details are requested to elucidate the basis of the motor defects, which are the first to appear during KD onset. Here we use transmission electron microscopy (TEM) to focus on the alterations produced by KD in the lower motor system at postnatal day 15 (P15), a nearly asymptomatic stage, and in the juvenile P30 mouse. We find mild effects on motorneuron soma, severe ones on sciatic nerves and very severe effects on nerve terminals and neuromuscular junctions at P30, with peripheral damage being already detectable at P15. Finally, we find that the gastrocnemius muscle undergoes atrophy and structural changes that are independent of denervation at P15. Our data further characterize the ultrastructural analysis of the KD mouse model, and support recent theories of a dying-back mechanism for neuronal degeneration, which is independent of demyelination.

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is thatthere is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the completeprocess including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increasedautophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in manycases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as forreviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multipleassays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagyrelated protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

Background The integration of graphene in photovoltaic modules, fuel cells, batteries, supercapacitors, and devices for hydrogen generation offers opportunities to tackle challenges driven by the increasing global energy demand. Graphene’s two-dimensional (2D) nature leads to a theoretical surface-to-mass ratio of ~2600 m 2 /g, which combined with its high electrical conductivity and flexibility, gives it the potential to store electric charge, ions, or hydrogen. Other 2D crystals, such as transition metal chalcogenides (TMDs) and transition metal oxides, are also promising and are now gaining increasing attention for energy applications. The advantage of using such 2D crystals is linked to the possibility of creating and designing layered artificial structures with “on-demand” properties by means of spin-on processes, or layer-by-layer assembly. This approach exploits the availability of materials with metallic, semiconducting, and insulating properties. Advances The success of graphene and related materials (GRMs) for energy applications crucially depends on the development and optimization of production methods. High-volume liquid-phase exfoliation is being developed for a wide variety of layered materials. This technique is being optimized to control the flake size and to increase the edge-to-surface ratio, which is crucial for optimizing electrode performance in fuel cells and batteries. Micro- or nanocrystal or flake edge control can also be achieved through chemical synthesis. This is an ideal route for functionalization, in order to improve storage capacity. Large-area growth via chemical vapor deposition (CVD) has been demonstrated, producing material with high structural and electronic quality for the preparation of transparent conducting electrodes for displays and touch-screens, and is being evaluated for photovoltaic applications. CVD growth of other multicomponent layered materials is less mature and needs further development. Although many transfer techniques have been developed successfully, further improvement of high-volume manufacturing and transfer processes for multilayered heterostructures is needed. In this context, layer-by-layer assembly may enable the realization of devices with on-demand properties for targeted applications, such as photovoltaic devices in which photon absorption in TMDs is combined with charge transport in graphene. Outlook Substantial progress has been made on the preparation of GRMs at the laboratory level. However, cost-effective production of GRMs on an industrial scale is needed to create the future energy value chain. Applications that could benefit the most from GRMs include flexible electronics, batteries with efficient anodes and cathodes, supercapacitors with high energy density, and solar cells. The realization of GRMs with specific transport and insulating properties on demand is an important goal. Additional energy applications of GRMs comprise water splitting and hydrogen production. As an example, the edges of MoS 2 single layers can oxidize fuels—such as hydrogen, methanol, and ethanol—in fuel cells, and GRM membranes can be used in fuel cells to improve proton exchange. Functionalized graphene can be exploited for water splitting and hydrogen production. Flexible and wearable devices and membranes incorporating GRMs can also generate electricity from motion, as well as from water and gas flows. Tailored GRMs for energy applications. The ability to produce GRMs with desired specific properties paves the way to their integration in a variety of energy devices. Solution processing and chemical vapor deposition are the ideal means to produce thin films that can be used as electrodes in energy devices (such as solar panels, batteries, fuel cells, or in hydrogen storage). Chemical synthesis is an attractive route to produce “active” elements in solar cell or thermoelectric devices.

We present the science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems, targeting an evolution in technology, that might lead to impacts and benefits reaching into most areas of society. This roadmap was developed within the framework of the European Graphene Flagship and outlines the main targets and research areas as best understood at the start of this ambitious project. We provide an overview of the key aspects of graphene and related materials (GRMs), ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries. We also define an extensive list of acronyms in an effort to standardize the nomenclature in this emerging field.

Perovskite solar cells based on abundant low cost materials promise to compete on performance with mainstream PV. Here we demonstrate lead-free perovskite solar cells, removing a potential barrier to widespread deployment.

Circular RNAs (circRNAs) constitute a family of transcripts with unique structures and still largely unknown functions. Their biogenesis, which proceeds via a back-splicing reaction, is fairly well characterized, whereas their role in the modulation of physiologically relevant processes is still unclear. Here we performed expression profiling of circRNAs during in vitro differentiation of murine and human myoblasts, and we identified conserved species regulated in myogenesis and altered in Duchenne muscular dystrophy. A high-content functional genomic screen allowed the study of their functional role in muscle differentiation. One of them, circ-ZNF609, resulted in specifically controlling myoblast proliferation. Circ-ZNF609 contains an open reading frame spanning from the start codon, in common with the linear transcript, and terminating at an in-frame STOP codon, created upon circularization. Circ-ZNF609 is associated with heavy polysomes, and it is translated into a protein in a splicing-dependent and cap-independent manner, providing an example of a protein-coding circRNA in eukaryotes.

We demonstrate that, via controlled anion exchange reactions using a range of different halide precursors, we can finely tune the chemical composition and the optical properties of presynthesized colloidal cesium lead halide perovskite nanocrystals (NCs), from green emitting CsPbBr3 to bright emitters in any other region of the visible spectrum, and back, by displacement of Cl(-) or I(-) ions and reinsertion of Br(-) ions. This approach gives access to perovskite semiconductor NCs with both structural and optical qualities comparable to those of directly synthesized NCs. We also show that anion exchange is a dynamic process that takes place in solution between NCs. Therefore, by mixing solutions containing perovskite NCs emitting in different spectral ranges (due to different halide compositions) their mutual fast exchange dynamics leads to homogenization in their composition, resulting in NCs emitting in a narrow spectral region that is intermediate between those of the parent nanoparticles.

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of μs), very high dynamic range (140 dB versus 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world.

This review highlights the recent research advances in active nanostructured anode materials for the next generation of Li-ion batteries (LIBs). In fact, in order to address both energy and power demands of secondary LIBs for future energy storage applications, it is required the development of innovative kinds of electrodes. Nanostructured materials based on carbon, metal/semiconductor, metal oxides and metal phosphides/nitrides/sulfides show a variety of admirable properties for LIBs applications such as high surface area, low diffusion distance, high electrical and ionic conductivity. Therefore, nanosized active materials are extremely promising for bridging the gap towards the realization of the next generation of LIBs with high reversible capacities, increased power capability, long cycling stability and free from safety concerns. In this review, anode materials are classified, depending on their electrochemical reaction with lithium, into three groups: intercalation/de-intercalation, alloy/de-alloy and conversion materials. Furthermore, the effect of nanoscale size and morphology on the electrochemical performance is presented. Synthesis of the nanostructures, lithium battery performance and electrode reaction mechanisms are also discussed. To conclude, the main aim of this review is to provide an organic outline of the wide range of recent research progresses and perspectives on nanosized active anode materials for future LIBs.

Electronic Textiles (e-textiles) are fabrics that feature electronics and interconnections woven into them, presenting physical flexibility and typical size that cannot be achieved with other existing electronic manufacturing techniques. Components and interconnections are intrinsic to the fabric and thus are less visible and not susceptible of becoming tangled or snagged by surrounding objects. E-textiles can also more easily adapt to fast changes in the computational and sensing requirements of any specific application, this one representing a useful feature for power management and context awareness. The vision behind wearable computing foresees future electronic systems to be an integral part of our everyday outfits. Such electronic devices have to meet special requirements concerning wearability. Wearable systems will be characterized by their ability to automatically recognize the activity and the behavioral status of their own user as well as of the situation around her/him, and to use this information to adjust the systems' configuration and functionality. This review focuses on recent advances in the field of Smart Textiles and pays particular attention to the materials and their manufacturing process. Each technique shows advantages and disadvantages and our aim is to highlight a possible trade-off between flexibility, ergonomics, low power consumption, integration and eventually autonomy.

Abstract Despite the impressive photovoltaic performances with power conversion efficiency beyond 22%, perovskite solar cells are poorly stable under operation, failing by far the market requirements. Various technological approaches have been proposed to overcome the instability problem, which, while delivering appreciable incremental improvements, are still far from a market-proof solution. Here we show one-year stable perovskite devices by engineering an ultra-stable 2D/3D (HOOC(CH 2 ) 4 NH 3 ) 2 PbI 4 /CH 3 NH 3 PbI 3 perovskite junction. The 2D/3D forms an exceptional gradually-organized multi-dimensional interface that yields up to 12.9% efficiency in a carbon-based architecture, and 14.6% in standard mesoporous solar cells. To demonstrate the up-scale potential of our technology, we fabricate 10 × 10 cm 2 solar modules by a fully printable industrial-scale process, delivering 11.2% efficiency stable for >10,000 h with zero loss in performances measured under controlled standard conditions. This innovative stable and low-cost architecture will enable the timely commercialization of perovskite solar cells.

Lithium-ion batteries, which power portable electronics, electric vehicles, and stationary storage, have been recognized with the 2019 Nobel Prize in chemistry. The development of nanomaterials and their related processing into electrodes and devices can improve the performance and/or development of the existing energy storage systems. We provide a perspective on recent progress in the application of nanomaterials in energy storage devices, such as supercapacitors and batteries. The versatility of nanomaterials can lead to power sources for portable, flexible, foldable, and distributable electronics; electric transportation; and grid-scale storage, as well as integration in living environments and biomedical systems. To overcome limitations of nanomaterials related to high reactivity and chemical instability caused by their high surface area, nanoparticles with different functionalities should be combined in smart architectures on nano- and microscales. The integration of nanomaterials into functional architectures and devices requires the development of advanced manufacturing approaches. We discuss successful strategies and outline a roadmap for the exploitation of nanomaterials for enabling future energy storage applications, such as powering distributed sensor networks and flexible and wearable electronics.

Abstract Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Starting from human ¿sense of touch,¿ this paper reviews the state of tactile sensing in robotics. The physiology, coding, and transferring tactile data and perceptual importance of the ¿sense of touch¿ in humans are discussed. Following this, a number of design hints derived for robotic tactile sensing are presented. Various technologies and transduction methods used to improve the touch sense capability of robots are presented. Tactile sensing, focused to fingertips and hands until past decade or so, has now been extended to whole body, even though many issues remain open. Trend and methods to develop tactile sensing arrays for various body sites are presented. Finally, various system issues that keep tactile sensing away from widespread utility are discussed.

Metal halide perovskites represent a flourishing area of research, which is driven by both their potential application in photovoltaics and optoelectronics and by the fundamental science behind their unique optoelectronic properties. The emergence of new colloidal methods for the synthesis of halide perovskite nanocrystals, as well as the interesting characteristics of this new type of material, has attracted the attention of many researchers. This review aims to provide an up-to-date survey of this fast-moving field and will mainly focus on the different colloidal synthesis approaches that have been developed. We will examine the chemistry and the capability of different colloidal synthetic routes with regard to controlling the shape, size, and optical properties of the resulting nanocrystals. We will also provide an up-to-date overview of their postsynthesis transformations, and summarize the various solution processes that are aimed at fabricating halide perovskite-based nanocomposites. Furthermore, we will review the fundamental optical properties of halide perovskite nanocrystals by focusing on their linear optical properties, on the effects of quantum confinement, and on the current knowledge of their exciton binding energies. We will also discuss the emergence of nonlinear phenomena such as multiphoton absorption, biexcitons, and carrier multiplication. Finally, we will discuss open questions and possible future directions.

Relational machine learning studies methods for the statistical analysis of relational, or graph-structured, data. In this paper, we provide a review of how such statistical models can be “trained” on large knowledge graphs, and then used to predict new facts about the world (which is equivalent to predicting new edges in the graph). In particular, we discuss two fundamentally different kinds of statistical relational models, both of which can scale to massive data sets. The first is based on latent feature models such as tensor factorization and multiway neural networks. The second is based on mining observable patterns in the graph. We also show how to combine these latent and observable models to get improved modeling power at decreased computational cost. Finally, we discuss how such statistical models of graphs can be combined with text-based information extraction methods for automatically constructing knowledge graphs from the Web. To this end, we also discuss Google's knowledge vault project as an example of such combination.

In this paper, we present an appearance-based method for person re-identification. It consists in the extraction of features that model three complementary aspects of the human appearance: the overall chromatic content, the spatial arrangement of colors into stable regions, and the presence of recurrent local motifs with high entropy. All this information is derived from different body parts, and weighted opportunely by exploiting symmetry and asymmetry perceptual principles. In this way, robustness against very low resolution, occlusions and pose, viewpoint and illumination changes is achieved. The approach applies to situations where the number of candidates varies continuously, considering single images or bunch of frames for each individual. It has been tested on several public benchmark datasets (ViPER, iLIDS, ETHZ), gaining new state-of-the-art performances.

The proliferation of soft robotics research worldwide has brought substantial achievements in terms of principles, models, technologies, techniques, and prototypes of soft robots. Such achievements are reviewed here in terms of the abilities that they provide robots that were not possible before. An analysis of the evolution of this field shows how, after a few pioneering works in the years 2009 to 2012, breakthrough results were obtained by taking seminal technological and scientific challenges related to soft robotics from actuation and sensing to modeling and control. Further progress in soft robotics research has produced achievements that are important in terms of robot abilities-that is, from the viewpoint of what robots can do today thanks to the soft robotics approach. Abilities such as squeezing, stretching, climbing, growing, and morphing would not be possible with an approach based only on rigid links. The challenge ahead for soft robotics is to further develop the abilities for robots to grow, evolve, self-heal, develop, and biodegrade, which are the ways that robots can adapt their morphology to the environment.

Metal-halide perovskites have rapidly emerged as one of the most promising materials of the 21st century, with many exciting properties and great potential for a broad range of applications, from photovoltaics to optoelectronics and photocatalysis. The ease with which metal-halide perovskites can be synthesized in the form of brightly luminescent colloidal nanocrystals, as well as their tunable and intriguing optical and electronic properties, has attracted researchers from different disciplines of science and technology. In the last few years, there has been a significant progress in the shape-controlled synthesis of perovskite nanocrystals and understanding of their properties and applications. In this comprehensive review, researchers having expertise in different fields (chemistry, physics, and device engineering) of metal-halide perovskite nanocrystals have joined together to provide a state of the art overview and future prospects of metal-halide perovskite nanocrystal research.

Cephalopods such as octopuses have a combination of a stretchable skin and color-tuning organs to control both posture and color for visual communication and disguise. We present an electroluminescent material that is capable of large uniaxial stretching and surface area changes while actively emitting light. Layers of transparent hydrogel electrodes sandwich a ZnS phosphor-doped dielectric elastomer layer, creating thin rubber sheets that change illuminance and capacitance under deformation. Arrays of individually controllable pixels in thin rubber sheets were fabricated using replica molding and were subjected to stretching, folding, and rolling to demonstrate their use as stretchable displays. These sheets were then integrated into the skin of a soft robot, providing it with dynamic coloration and sensory feedback from external and internal stimuli.